Signaling method for chroma intra prediction mode

ABSTRACT

A method, computer program, and computer system is provided for encoding or decoding video data. Video data including a chroma component and a luma component is received. One or more contexts for entropy coding chroma intra prediction modes are identified based on a co-located luma block at one or more pre-defined positions. The video data is decoded based on the identified contexts.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority from U.S. Provisional PatentApplication No. 63/026,495, filed on May 18, 2020, in the U.S. Patentand Trademark Office, which is incorporated herein by reference in itsentirety.

FIELD

This disclosure relates generally to field of data processing, and moreparticularly to video encoding and/or decoding.

BACKGROUND

AOMedia Video 1 (AV1) is an open video coding format designed for videotransmissions over the Internet. It was developed as a successor to VP9by the Alliance for Open Media (AOMedia), a consortium founded in 2015that includes semiconductor firms, video on demand providers, videocontent producers, software development companies and web browservendors. Many of the components of the AV1 project were sourced fromprevious research efforts by Alliance members. Individual contributorsstarted experimental technology platforms years before: Xiph's/Mozilla'sDaala already published code in 2010, Google's experimental VP9evolution project VP10 was announced on 12 Sep. 2014, and Cisco's Thorwas published on 11 Aug. 2015. Building on the codebase of VP9, AV1incorporates additional techniques, several of which were developed inthese experimental formats. The first version 0.1.0 of the AV1 referencecodec was published on 7 Apr. 2016. The Alliance announced the releaseof the AV1 bitstream specification on 28 Mar. 2018, along with areference, software-based encoder and decoder. On 25 Jun. 2018, avalidated version 1.0.0 of the specification was released. On 8 Jan.2019 a validated version 1.0.0 with Errata 1 of the specification wasreleased. The AV1 bitstream specification includes a reference videocodec.

SUMMARY

Embodiments relate to a method, system, and computer readable medium forencoding and/or decoding video data. According to one aspect, a methodfor encoding and/or decoding video data is provided. The method mayinclude receiving video data including a chroma component and a lumacomponent is received. One or more contexts for entropy coding chromaintra prediction modes are identified based on a co-located luma blockat one or more multiples of pre-defined positions. The video data isdecoded based on the identified contexts.

According to another aspect, a computer system for encoding and/ordecoding video data is provided. The computer system may include one ormore processors, one or more computer-readable memories, one or morecomputer-readable tangible storage devices, and program instructionsstored on at least one of the one or more storage devices for executionby at least one of the one or more processors via at least one of theone or more memories, whereby the computer system is capable ofperforming a method. The method may include receiving video dataincluding a chroma component and a luma component is received. One ormore contexts for entropy coding chroma intra prediction modes areidentified based on a co-located luma block at one or more multiples ofpre-defined positions. The video data is decoded based on the identifiedcontexts.

According to yet another aspect, a computer readable medium for encodingand/or decoding video data is provided. The computer readable medium mayinclude one or more computer-readable storage devices and programinstructions stored on at least one of the one or more tangible storagedevices, the program instructions executable by a processor. The programinstructions are executable by a processor for performing a method thatmay accordingly include receiving video data including a chromacomponent and a luma component is received. One or more contexts forentropy coding chroma intra prediction modes are identified based on aco-located luma block at one or more multiples of pre-defined positions.The video data is decoded based on the identified contexts.

BRIEF DESCRIPTION OF THE DRAWINGS

These and other objects, features and advantages will become apparentfrom the following detailed description of illustrative embodiments,which is to be read in connection with the accompanying drawings. Thevarious features of the drawings are not to scale as the illustrationsare for clarity in facilitating the understanding of one skilled in theart in conjunction with the detailed description. In the drawings:

FIG. 1 illustrates a networked computer environment according to atleast one embodiment;

FIG. 2 is a diagram of coding tree structures of the chroma componentand luma component of video data, according to at least one embodiment;

FIG. 3 is an operational flowchart illustrating the steps carried out bya program that codes video data, according to at least one embodiment;

FIG. 4 is a block diagram of internal and external components ofcomputers and servers depicted in FIG. 1 according to at least oneembodiment;

FIG. 5 is a block diagram of an illustrative cloud computing environmentincluding the computer system depicted in FIG. 1, according to at leastone embodiment; and

FIG. 6 is a block diagram of functional layers of the illustrative cloudcomputing environment of FIG. 5, according to at least one embodiment.

DETAILED DESCRIPTION

Detailed embodiments of the claimed structures and methods are disclosedherein; however, it can be understood that the disclosed embodiments aremerely illustrative of the claimed structures and methods that may beembodied in various forms. Those structures and methods may, however, beembodied in many different forms and should not be construed as limitedto the exemplary embodiments set forth herein. Rather, these exemplaryembodiments are provided so that this disclosure will be thorough andcomplete and will fully convey the scope to those skilled in the art. Inthe description, details of well-known features and techniques may beomitted to avoid unnecessarily obscuring the presented embodiments.

Embodiments relate generally to the field of data processing, and moreparticularly to video encoding and decoding. The following describedexemplary embodiments provide a system, method and computer program to,among other things, encode and/or decode video data based on a contextassociated with a co-located luma block at one or more pre-definedpositions. Therefore, some embodiments have the capacity to improve thefield of computing by improving encoding and decoding efficiency throughthe use of improved signaling for a chroma intra prediction mode.

As previously described, AOMedia Video 1 (AV1) is an open video codingformat designed for video transmissions over the Internet. It wasdeveloped as a successor to VP9 by the Alliance for Open Media(AOMedia), a consortium founded in 2015 that includes semiconductorfirms, video on demand providers, video content producers, softwaredevelopment companies and web browser vendors. Many of the components ofthe AV1 project were sourced from previous research efforts by Alliancemembers. Individual contributors started experimental technologyplatforms years before: Xiph's/Mozilla's Daala already published code in2010, Google's experimental VP9 evolution project VP10 was announced on12 Sep. 2014, and Cisco's Thor was published on 11 Aug. 2015. Buildingon the codebase of VP9, AV1 incorporates additional techniques, severalof which were developed in these experimental formats. The first version0.1.0 of the AV1 reference codec was published on 7 Apr. 2016. TheAlliance announced the release of the AV1 bitstream specification on 28Mar. 2018, along with a reference, software-based encoder and decoder.On 25 Jun. 2018, a validated version 1.0.0 of the specification wasreleased. On 8 Jan. 2019 a validated version 1.0.0 with Errata 1 of thespecification was released. The AV1 bitstream specification includes areference video codec.

In AV1, semi decoupled partitioning (SDP) may be used. However, in SDP,luma and chroma blocks in one super block can have different partitions,and the area of one chroma block may cover multiple luma coding blocks,so it may not be optimal to always use top-left position of chroma blockto locate the corresponding luma mode. Additionally, when luma andchroma blocks in one super block have different partitions, CfL mode hasa higher chance to be selected as the best mode, but this characteristicis not well exploited in the chroma mode signaling method. Moreover,when signaling chroma intra prediction modes, the luma modes within thecurrent super block are all available. But this is not exploited todesign the better codewords for signaling the chroma intra predictionmodes. It may be advantageous, therefore, to identify one or morecontexts for entropy coding chroma intra prediction modes based on aco-located luma block at one or more pre-defined positions for improvedsignaling for chroma intra prediction mode are proposed.

Aspects are described herein with reference to flowchart illustrationsand/or block diagrams of methods, apparatus (systems), and computerreadable media according to the various embodiments. It will beunderstood that each block of the flowchart illustrations and/or blockdiagrams, and combinations of blocks in the flowchart illustrationsand/or block diagrams, can be implemented by computer readable programinstructions.

Referring now to FIG. 1, a functional block diagram of a networkedcomputer environment illustrating a video coding system 100 (hereinafter“system”) for encoding and/or decoding video data based on coding treestructure types. It should be appreciated that FIG. 1 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environments may be madebased on design and implementation requirements.

The system 100 may include a computer 102 and a server computer 114. Thecomputer 102 may communicate with the server computer 114 via acommunication network 110 (hereinafter “network”). The computer 102 mayinclude a processor 104 and a software program 108 that is stored on adata storage device 106 and is enabled to interface with a user andcommunicate with the server computer 114. As will be discussed belowwith reference to FIG. 4 the computer 102 may include internalcomponents 800A and external components 900A, respectively, and theserver computer 114 may include internal components 800B and externalcomponents 900B, respectively. The computer 102 may be, for example, amobile device, a telephone, a personal digital assistant, a netbook, alaptop computer, a tablet computer, a desktop computer, or any type ofcomputing devices capable of running a program, accessing a network, andaccessing a database.

The server computer 114 may also operate in a cloud computing servicemodel, such as Software as a Service (SaaS), Platform as a Service(PaaS), or Infrastructure as a Service (laaS), as discussed below withrespect to FIGS. 6 and 7. The server computer 114 may also be located ina cloud computing deployment model, such as a private cloud, communitycloud, public cloud, or hybrid cloud.

The server computer 114, which may be used for encoding video data isenabled to run a Video Coding Program 116 (hereinafter “program”) thatmay interact with a database 112. The Video Coding Program method isexplained in more detail below with respect to FIG. 3. In oneembodiment, the computer 102 may operate as an input device including auser interface while the program 116 may run primarily on servercomputer 114. In an alternative embodiment, the program 116 may runprimarily on one or more computers 102 while the server computer 114 maybe used for processing and storage of data used by the program 116. Itshould be noted that the program 116 may be a standalone program or maybe integrated into a larger video coding program.

It should be noted, however, that processing for the program 116 may, insome instances be shared amongst the computers 102 and the servercomputers 114 in any ratio. In another embodiment, the program 116 mayoperate on more than one computer, server computer, or some combinationof computers and server computers, for example, a plurality of computers102 communicating across the network 110 with a single server computer114. In another embodiment, for example, the program 116 may operate ona plurality of server computers 114 communicating across the network 110with a plurality of client computers. Alternatively, the program mayoperate on a network server communicating across the network with aserver and a plurality of client computers.

The network 110 may include wired connections, wireless connections,fiber optic connections, or some combination thereof. In general, thenetwork 110 can be any combination of connections and protocols thatwill support communications between the computer 102 and the servercomputer 114. The network 110 may include various types of networks,such as, for example, a local area network (LAN), a wide area network(WAN) such as the Internet, a telecommunication network such as thePublic Switched Telephone Network (PSTN), a wireless network, a publicswitched network, a satellite network, a cellular network (e.g., a fifthgeneration (5G) network, a long-term evolution (LTE) network, a thirdgeneration (3G) network, a code division multiple access (CDMA) network,etc.), a public land mobile network (PLMN), a metropolitan area network(MAN), a private network, an ad hoc network, an intranet, a fiberoptic-based network, or the like, and/or a combination of these or othertypes of networks.

The number and arrangement of devices and networks shown in FIG. 1 areprovided as an example. In practice, there may be additional devicesand/or networks, fewer devices and/or networks, different devices and/ornetworks, or differently arranged devices and/or networks than thoseshown in FIG. 1. Furthermore, two or more devices shown in FIG. 1 may beimplemented within a single device, or a single device shown in FIG. 1may be implemented as multiple, distributed devices. Additionally, oralternatively, a set of devices (e.g., one or more devices) of system100 may perform one or more functions described as being performed byanother set of devices of system 100.

Referring now to FIG. 2, a block diagram 200 of an exemplary coding treestructure for the video data is depicted. The coding tree structure mayinclude a luma component 202 and a chroma component 204.

A semi decoupled partitioning (SDP) scheme (i.e., semi separate tree(SST) or flexible block partitioning for chroma component) may be used.According to SDP, the luma component 202 and the chroma component 204 inone super block (SB) may have the same or different block partitioning,which may be dependent on the luma coded block sizes or the luma treedepth. When the luma block area size is greater than one threshold T1 orcoding tree splitting depth of luma block is smaller than or equal toone threshold T2, then the chroma block may use the same coding treestructure as luma. Otherwise when the block area size is smaller than orequal to T1 or luma splitting depth is larger than T2, the correspondingchroma block can have different coding block partitioning with lumacomponent, which may be called flexible block partitioning for chromacomponent. T1 may be a positive integer, such as 128 or 256. T2 may be apositive integer, such as 1 or 2.

According to one or more embodiments, when SDP may be applied and onechroma coding block may be associated with multiple luma coding blocks,the contexts used for entropy coding the chroma intra prediction modesmay be dependent on the corresponding luma block located at one or morepre-defined positions. In one embodiment, the one or more pre-definedpositions may include middle position and/or top-left corner of currentchroma block. In one embodiment, the middle position of the currentchroma block may be the top-left corner of the current chroma block.

In one embodiment, when the middle position and top-left corner ofcurrent chroma block may be both used to locate the corresponding lumablock, then these two luma modes may be quantized before performingcontext selection. In one embodiment, luma modes may be quantized to twovalues before performing context selection process, which may be adirectional mode or a non-directional mode.

In another embodiment, non-directional modes may be quantized to onesingle value, and directional modes may be quantized to a smaller setaccording to their angles. In one example, directional modes may bequantized to 4 values, 0 means the angle of current mode may be equal tosmaller than 90 degree, 1 means the angle of current mode may be between90 degree to 135 degrees, 2 means the angle of current mode may bebetween 135 degree to 180 degrees, 3 means the angle of current mode maybe larger than 180 degrees.

In one embodiment, the context may be derived as the intra predictionmode that may be used to predict most of samples in co-located lumablock.

In one embodiment, multiple sample positions may be pre-defined, and theintra prediction modes associated with these positions for predictingthe co-located luma block may be identified, then one of theseidentified prediction modes may be used to derive the context value. Inone example, the prediction mode that may be used most frequently amongthe identified prediction modes may be used to derive the context value.In a second example, the pre-defined sample positions include the fourcorner samples and the center/middle sample. In a third example, thepre-defined sample positions include the four corner samples. In afourth example, the pre-defined sample positions include two selectedpositions of the four corner samples and one center/middle sample. In afifth example, the pre-defined sample positions include three selectedpositions of the four corner samples and one center/middle sample.

In one embodiment, if the co-located luma block at one or morepre-defined positions may be not predicted by intra prediction mode andthe current chroma coding block may be predicted by intra predictionmode, then the prediction modes of co-located one or multiple luma blockmay be mapped to one or multiple pre-defined intra prediction modes. Inone example, when the co-located luma block may be coded by IBC orPalette mode, then a default intra prediction mode may be used to derivethe context for entropy coding the chroma intra prediction mode. Thesaid default intra prediction mode include, but not limited to DC,SMOOTH, SMOOTH-H, SMOOTH-V, or Paeth prediction mode.

According to one or more embodiments, when signaling the chroma intraprediction modes, one flag, namely CfL flag, may be firstly signaled toindicate whether current chroma mode may be CfL mode or not. In oneembodiment, chroma intra prediction modes of neighboring blocks may beused to derive the context for signaling the CfL flag. In one example,when none of the neighboring chroma modes may be CfL modes, the firstcontext may be used. Otherwise, the second context may be used. Inanother example, when none of the neighboring chroma modes may be CfLmodes, the first context may be used. Otherwise, when one of theneighboring chroma modes may be CfL mode, the second context may beused. Otherwise, the third context may be used.

In one embodiment, the corresponding luma mode may be used to derive thecontext for signaling the CfL flag. In one embodiment, the coordinate ofthe corresponding luma mode may be located at middle position andtop-left corner of current chroma block. In another embodiment, when thecorresponding luma mode may be directional modes, the first context maybe used. Otherwise, the second context may be used. In anotherembodiment, when two corresponding luma modes may be employed todetermine the context of CfL flag, 3 contexts may be used. When bothcorresponding luma modes may be non-directional mode, the first contextmay be used. Otherwise, when one of the corresponding luma mode may benon-directional mode, the second context may be used. Otherwise, thethird context may be used.

According to one or more embodiments, for signaling chroma intraprediction modes, one list may be constructed, which include thepreviously encoded luma modes within current picture/slice/tile. Onlythe N luma modes with the highest occurrence may be allowed andsignalled for current chroma block, wherein N may be a positive integer.In one embodiment, N may be power of 2 value. In one embodiment, onlythe previously encoded luma modes within current super block row can beused. In one embodiment, when SDP may be enabled, only the previouslyencoded luma modes within current super block can be used.

According to one or more embodiments, all nominal intra predictionangles allowed for luma coded blocks may also be allowed and signaledfor chroma coded blocks, whereas only a subset of delta angles to thenominal angles may be allowed and signaled for chroma intra codedblocks. In one embodiment, all the non-directional modes, such as DC,SMOOTH, SMOOTH-H, SMOOTH-V modes, may be allowed and signaled for chromaintra coded blocks. In one embodiment only the delta angles to theco-located luma intra prediction modes may be allowed and signaled forthe chroma coded blocks. In one embodiment, the nominal angles may befirstly signaled together with non-directional modes. After that, ifcurrent mode may be directional mode and equal to co-located lumanominal modes, the second flag may be signaled to indicate the index ofdelta angle to the nominal angle. In another embodiment, all the allowedintra prediction modes for chroma coded blocks may be signaled together.

Referring now to FIG. 3, an operational flowchart illustrating the stepsof a method 300 for encoding and/or decoding video data is depicted. Insome implementations, one or more process blocks of FIG. 3 may beperformed by the computer 102 (FIG. 1) and the server computer 114 (FIG.1). In some implementations, one or more process blocks of FIG. 3 may beperformed by another device or a group of devices separate from orincluding the computer 102 and the server computer 114.

At 302, the method 300 includes receiving video data including a chromacomponent and a luma component.

At 304, the method 300 includes identifying one or more contexts forentropy-coding chroma intra prediction modes based on a co-located lumablock at one or more pre-defined positions.

At 306, the method 300 includes decoding the video data based on theidentified contexts.

It may be appreciated that FIG. 3 provides only an illustration of oneimplementation and does not imply any limitations with regard to howdifferent embodiments may be implemented. Many modifications to thedepicted environments may be made based on design and implementationrequirements.

FIG. 4 is a block diagram 400 of internal and external components ofcomputers depicted in FIG. 1 in accordance with an illustrativeembodiment. It should be appreciated that FIG. 4 provides only anillustration of one implementation and does not imply any limitationswith regard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environments may be madebased on design and implementation requirements.

Computer 102 (FIG. 1) and server computer 114 (FIG. 1) may includerespective sets of internal components 800A,B and external components900A,B illustrated in FIG. 4. Each of the sets of internal components800 include one or more processors 820, one or more computer-readableRAMs 822 and one or more computer-readable ROMs 824 on one or more buses826, one or more operating systems 828, and one or morecomputer-readable tangible storage devices 830.

Processor 820 is implemented in hardware, firmware, or a combination ofhardware and software. Processor 820 is a central processing unit (CPU),a graphics processing unit (GPU), an accelerated processing unit (APU),a microprocessor, a microcontroller, a digital signal processor (DSP), afield-programmable gate array (FPGA), an application-specific integratedcircuit (ASIC), or another type of processing component. In someimplementations, processor 820 includes one or more processors capableof being programmed to perform a function. Bus 826 includes a componentthat permits communication among the internal components 800A,B.

The one or more operating systems 828, the software program 108 (FIG. 1)and the Video Coding Program 116 (FIG. 1) on server computer 114(FIG. 1) are stored on one or more of the respective computer-readabletangible storage devices 830 for execution by one or more of therespective processors 820 via one or more of the respective RAMs 822(which typically include cache memory). In the embodiment illustrated inFIG. 4, each of the computer-readable tangible storage devices 830 is amagnetic disk storage device of an internal hard drive. Alternatively,each of the computer-readable tangible storage devices 830 is asemiconductor storage device such as ROM 824, EPROM, flash memory, anoptical disk, a magneto-optic disk, a solid state disk, a compact disc(CD), a digital versatile disc (DVD), a floppy disk, a cartridge, amagnetic tape, and/or another type of non-transitory computer-readabletangible storage device that can store a computer program and digitalinformation.

Each set of internal components 800A,B also includes a R/W drive orinterface 832 to read from and write to one or more portablecomputer-readable tangible storage devices 936 such as a CD-ROM, DVD,memory stick, magnetic tape, magnetic disk, optical disk orsemiconductor storage device. A software program, such as the softwareprogram 108 (FIG. 1) and the Video Coding Program 116 (FIG. 1) can bestored on one or more of the respective portable computer-readabletangible storage devices 936, read via the respective R/W drive orinterface 832 and loaded into the respective hard drive 830.

Each set of internal components 800A,B also includes network adapters orinterfaces 836 such as a TCP/IP adapter cards; wireless Wi-Fi interfacecards; or 3G, 4G, or 5G wireless interface cards or other wired orwireless communication links. The software program 108 (FIG. 1) and theVideo Coding Program 116 (FIG. 1) on the server computer 114 (FIG. 1)can be downloaded to the computer 102 (FIG. 1) and server computer 114from an external computer via a network (for example, the Internet, alocal area network or other, wide area network) and respective networkadapters or interfaces 836. From the network adapters or interfaces 836,the software program 108 and the Video Coding Program 116 on the servercomputer 114 are loaded into the respective hard drive 830. The networkmay comprise copper wires, optical fibers, wireless transmission,routers, firewalls, switches, gateway computers and/or edge servers.

Each of the sets of external components 900A,B can include a computerdisplay monitor 920, a keyboard 930, and a computer mouse 934. Externalcomponents 900A,B can also include touch screens, virtual keyboards,touch pads, pointing devices, and other human interface devices. Each ofthe sets of internal components 800A,B also includes device drivers 840to interface to computer display monitor 920, keyboard 930 and computermouse 934. The device drivers 840, R/W drive or interface 832 andnetwork adapter or interface 836 comprise hardware and software (storedin storage device 830 and/or ROM 824).

It is understood in advance that although this disclosure includes adetailed description on cloud computing, implementation of the teachingsrecited herein are not limited to a cloud computing environment. Rather,some embodiments are capable of being implemented in conjunction withany other type of computing environment now known or later developed.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client devices through athin client interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (laaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring to FIG. 5, illustrative cloud computing environment 500 isdepicted. As shown, cloud computing environment 500 comprises one ormore cloud computing nodes 10 with which local computing devices used bycloud consumers, such as, for example, personal digital assistant (PDA)or cellular telephone 54A, desktop computer 54B, laptop computer 54C,and/or automobile computer system 54N may communicate. Cloud computingnodes 10 may communicate with one another. They may be grouped (notshown) physically or virtually, in one or more networks, such asPrivate, Community, Public, or Hybrid clouds as described hereinabove,or a combination thereof. This allows cloud computing environment 600 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 54A-N shownin FIG. 5 are intended to be illustrative only and that cloud computingnodes 10 and cloud computing environment 500 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Referring to FIG. 6, a set of functional abstraction layers 600 providedby cloud computing environment 500 (FIG. 5) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments are notlimited thereto. As depicted, the following layers and correspondingfunctions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage devices 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and Video Coding 96. Video Coding 96 mayencode and/or decode video data based on a context associated with aco-located luma block at one or more pre-defined positions.

Some embodiments may relate to a system, a method, and/or a computerreadable medium at any possible technical detail level of integration.The computer readable medium may include a computer-readablenon-transitory storage medium (or media) having computer readableprogram instructions thereon for causing a processor to carry outoperations.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program code/instructions for carrying out operationsmay be assembler instructions, instruction-set-architecture (ISA)instructions, machine instructions, machine dependent instructions,microcode, firmware instructions, state-setting data, configuration datafor integrated circuitry, or either source code or object code writtenin any combination of one or more programming languages, including anobject oriented programming language such as Smalltalk, C++, or thelike, and procedural programming languages, such as the “C” programminglanguage or similar programming languages. The computer readable programinstructions may execute entirely on the user's computer, partly on theuser's computer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider). In some embodiments,electronic circuitry including, for example, programmable logiccircuitry, field-programmable gate arrays (FPGA), or programmable logicarrays (PLA) may execute the computer readable program instructions byutilizing state information of the computer readable programinstructions to personalize the electronic circuitry, in order toperform aspects or operations.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer readable media according to variousembodiments. In this regard, each block in the flowchart or blockdiagrams may represent a module, segment, or portion of instructions,which comprises one or more executable instructions for implementing thespecified logical function(s). The method, computer system, and computerreadable medium may include additional blocks, fewer blocks, differentblocks, or differently arranged blocks than those depicted in theFigures. In some alternative implementations, the functions noted in theblocks may occur out of the order noted in the Figures. For example, twoblocks shown in succession may, in fact, be executed concurrently orsubstantially concurrently, or the blocks may sometimes be executed inthe reverse order, depending upon the functionality involved. It willalso be noted that each block of the block diagrams and/or flowchartillustration, and combinations of blocks in the block diagrams and/orflowchart illustration, can be implemented by special purposehardware-based systems that perform the specified functions or acts orcarry out combinations of special purpose hardware and computerinstructions.

It will be apparent that systems and/or methods, described herein, maybe implemented in different forms of hardware, firmware, or acombination of hardware and software. The actual specialized controlhardware or software code used to implement these systems and/or methodsis not limiting of the implementations. Thus, the operation and behaviorof the systems and/or methods were described herein without reference tospecific software code—it being understood that software and hardwaremay be designed to implement the systems and/or methods based on thedescription herein.

No element, act, or instruction used herein should be construed ascritical or essential unless explicitly described as such. Also, as usedherein, the articles “a” and “an” are intended to include one or moreitems, and may be used interchangeably with “one or more.” Furthermore,as used herein, the term “set” is intended to include one or more items(e.g., related items, unrelated items, a combination of related andunrelated items, etc.), and may be used interchangeably with “one ormore.” Where only one item is intended, the term “one” or similarlanguage is used. Also, as used herein, the terms “has,” “have,”“having,” or the like are intended to be open-ended terms. Further, thephrase “based on” is intended to mean “based, at least in part, on”unless explicitly stated otherwise.

The descriptions of the various aspects and embodiments have beenpresented for purposes of illustration, but are not intended to beexhaustive or limited to the embodiments disclosed. Even thoughcombinations of features are recited in the claims and/or disclosed inthe specification, these combinations are not intended to limit thedisclosure of possible implementations. In fact, many of these featuresmay be combined in ways not specifically recited in the claims and/ordisclosed in the specification. Although each dependent claim listedbelow may directly depend on only one claim, the disclosure of possibleimplementations includes each dependent claim in combination with everyother claim in the claim set. Many modifications and variations will beapparent to those of ordinary skill in the art without departing fromthe scope of the described embodiments. The terminology used herein waschosen to best explain the principles of the embodiments, the practicalapplication or technical improvement over technologies found in themarketplace, or to enable others of ordinary skill in the art tounderstand the embodiments disclosed herein.

What is claimed is:
 1. A method of video coding, executable by aprocessor, comprising: receiving video data comprising a chromacomponent and a luma component; identifying one or more contexts forentropy coding chroma intra prediction modes corresponding to aco-located luma block at one or more pre-defined positions based on achroma block associated with the chroma component being associated withmultiple luma blocks associated with the luma component; decoding thevideo data based on the identified contexts; and signaling the chromaintra prediction modes, wherein the signaling of the chroma intraprediction modes is based on a luma mode list, wherein the luma modelist includes previously encoded luma modes with the highest occurrencewithin a current super block.
 2. The method of claim 1, wherein the oneor more pre-defined positions comprise one or more from among a middleposition and a top-left corner of a current chroma block.
 3. The methodof claim 2, wherein the middle position of the current chroma blockcorresponds to the top-left corner of a chroma block.
 4. The method ofclaim 1, further comprising: identifying one or more pre-defined samplepositions; identifying intra prediction modes associated with themultiple sample positions for predicting the co-located luma block; andderive the context value based on a prediction mode from among theidentified intra prediction modes.
 5. The method of claim 4 wherein amost-frequently used prediction mode from among the identifiedprediction modes is used to derive the context value.
 6. The method ofclaim 4, wherein the pre-defined sample positions include one or morecorner samples and a center sample.
 7. The method of claim 4, whereinthe pre-defined sample positions include four corner samples.
 8. Themethod of claim 1, further comprising mapping intra prediction modes toone or multiple pre-defined intra prediction modes based on theco-located luma block at the one or more pre-defined positions not beingpredicted by intra prediction mode and based on the current chromacoding block being predicted by intra prediction mode.
 9. The method ofclaim 8, wherein a default intra prediction mode is used to derive thecontext for entropy coding the chroma intra prediction modes based onthe co-located luma block being coded by intra-block copy or Palettemode.
 10. The method of claim 9, wherein the default intra predictionmode includes one or more from among DC, SMOOTH, SMOOTH-H, SMOOTH-V, andPaeth prediction modes.
 11. The method of claim 1, wherein based on thesignaling of the chroma intra prediction modes, a flag is signaled toindicate whether or not the current chroma mode is chroma-from-luma. 12.The method of claim 11, wherein a corresponding luma mode is used toderive the context for signaling the flag.
 13. The method of claim 1,wherein all nominal intra prediction angles allowed for luma codedblocks are allowed and signaled for chroma coded blocks.
 14. The methodof claim 13, wherein only a subset of delta angles to nominal angles areallowed and signaled for chroma intra coded blocks.
 15. The method ofclaim 14, wherein all non-directional modes are allowed and signaled forchroma intra coded blocks.
 16. The method of claim 14, wherein onlydelta angles corresponding to the co-located luma intra prediction modesare allowed and signaled for the chroma coded blocks.
 17. The method ofclaim 16, further comprising: signaling the nominal angles together withnon-directional modes; and signaling a second flag to indicate an indexof delta angle to the nominal angle based on the current mode being adirectional mode and equal to co-located luma nominal modes.
 18. Themethod of claim 16, wherein all the allowed intra prediction modes forchroma coded blocks are signaled together.
 19. A computer system fordecoding video data, the computer system comprising: one or morecomputer-readable non-transitory storage media configured to storecomputer program code; and one or more computer processors configured toaccess said computer program code and operate as instructed by saidcomputer program code, said computer program code including: receivingcode configured to cause the one or more computer processors to receivevideo data comprising a luma component and a chroma component;identifying code configured to cause the one or more computer processorsto identify one or more contexts for entropy coding chroma intraprediction modes corresponding to a co-located luma block at one or morepre-defined positions based on a chroma block associated with the chromacomponent being associated with multiple luma blocks associated with theluma component; decoding code configured to cause the one or morecomputer processors to decode the video data based on the identifiedcontexts; and signaling code configured to cause the one or moreprocessors to signal the chroma intra prediction modes, wherein thesignaling of the chroma intra prediction modes is based on a luma modelist, wherein the luma mode list includes previously encoded luma modeswith the highest occurrence within a current super block.
 20. Anon-transitory computer readable medium having stored thereon a computerprogram for decoding video data, the computer program configured tocause one or more computer processors to: receive video data comprisinga luma component and a chroma component; identify one or more contextsfor entropy coding chroma intra prediction modes corresponding to aco-located luma block at one or more pre-defined positions based on achroma block associated with the chroma component being associated withmultiple luma blocks associated with the luma component; decode thevideo data based on the identified contexts; and signal the chroma intraprediction modes, wherein the signaling of the chroma intra predictionmodes is based on a luma mode list, wherein the luma mode list includespreviously encoded luma modes with the highest occurrence within acurrent super block.